{"title":"正电子放射乳房x线照相术的病灶检测与定量","authors":"J. Qi, Ronald H. Huesman","doi":"10.1109/NSSMIC.2001.1009271","DOIUrl":null,"url":null,"abstract":"A Positron Emission Mammography (PEM) scanner dedicated to breast imaging is being developed at our laboratory. We have developed a fist mode likelihood reconstruction algorithm for this scanner. Here we theoretically study the lesion detection and quantitation. The lesion detectability is studied theoretically using computer observers. We found that for the zero-order quadratic prior, the region of interest observer can achieve the performance of the prewhitening observer with a properly selected smoothing parameter. We also study the lesion quantitation using the test statistic of the region of interest observer. The theoretical expressions for the bias, variance, and ensemble mean squared error of the quantitation are derived. Computer simulations show that the theoretical predictions are in good agreement with the Monte Carlo results for both lesion detection and quantitation.","PeriodicalId":159123,"journal":{"name":"2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Lesion detection and quantitation of positron emission mammography\",\"authors\":\"J. Qi, Ronald H. Huesman\",\"doi\":\"10.1109/NSSMIC.2001.1009271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Positron Emission Mammography (PEM) scanner dedicated to breast imaging is being developed at our laboratory. We have developed a fist mode likelihood reconstruction algorithm for this scanner. Here we theoretically study the lesion detection and quantitation. The lesion detectability is studied theoretically using computer observers. We found that for the zero-order quadratic prior, the region of interest observer can achieve the performance of the prewhitening observer with a properly selected smoothing parameter. We also study the lesion quantitation using the test statistic of the region of interest observer. The theoretical expressions for the bias, variance, and ensemble mean squared error of the quantitation are derived. Computer simulations show that the theoretical predictions are in good agreement with the Monte Carlo results for both lesion detection and quantitation.\",\"PeriodicalId\":159123,\"journal\":{\"name\":\"2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310)\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NSSMIC.2001.1009271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.2001.1009271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lesion detection and quantitation of positron emission mammography
A Positron Emission Mammography (PEM) scanner dedicated to breast imaging is being developed at our laboratory. We have developed a fist mode likelihood reconstruction algorithm for this scanner. Here we theoretically study the lesion detection and quantitation. The lesion detectability is studied theoretically using computer observers. We found that for the zero-order quadratic prior, the region of interest observer can achieve the performance of the prewhitening observer with a properly selected smoothing parameter. We also study the lesion quantitation using the test statistic of the region of interest observer. The theoretical expressions for the bias, variance, and ensemble mean squared error of the quantitation are derived. Computer simulations show that the theoretical predictions are in good agreement with the Monte Carlo results for both lesion detection and quantitation.